Climate science: Fine-tuning tropical cyclone trajectory predictions

The future trajectory of tropical cyclones can be predicted more accurately using a simple, statistical method described in Scientific Reports this week. The technique uses the statistical properties of deviations in tropical cyclone motion from a generally predictable mean trajectory, and could be used to complement other tropical cyclone forecast cones, especially before landfall.

Tropical cyclones, or hurricanes, are extreme atmospheric events that can be devastating upon landfall in populated areas. A number of schemes are used to predict their trajectories, including using knowledge of previous hurricanes in the same area and generating full-scale numerical simulations, but because hurricane trajectories tend to deviate from the predicted mean trajectory, these estimates can be imprecise.

Borrowing from the methodology of statistical physics, Hamid Kellay and colleagues show that these deviations from a hurricane’s mean trajectory can be modelled using a universal statistical law for their mean square displacement (MSD), a powerful tool to characterize random motion. The authors analyzed data from the US National Hurricane Center to show that the motion of the majority of hurricanes obeys the law for the MSD. They go on to use the scheme to accurately predict the actual corridors taken by Hurricane Ike, which hit the coast of Texas in 2008, and Hurricane Jimena, which made landfall on Mexico’s Pacific coast in 2009.

doi: 10.1038/srep00446

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